Area_based_analysis
Brandon Titensor
2025-01-08
1. Data Loading and Preprocessing
1.1 Edge Data
1.2 Surface Data
1.3 Calibration Wafer Data
1.4 Calibration Surface Data
2. Surface Area Distribution Analysis
3. Edge Area Distribution Analysis
4. Calibration Wafer Analysis - Edge
5. Calibration Surface Analysis
6. Edge Model Analysis
7. Straight Line Model (SLSM and SLCM)
8. Trial Anlysis
8.1 Trial 9
## Trial 9 Edge Distribution Analysis Results##
## 1. Correlation Analysis:## comparison pearson_r p_value
## cor Starshade Observed vs Calibration Observed 0.7027197 3.674915e-16
## cor1 Starshade Observed vs Model 0.9941039 2.254190e-96
## cor2 Starshade Observed vs SLSM Starshade 0.9973604 1.924980e-113
## cor3 Calibration Observed vs Model 0.6331472 1.569586e-12
## cor4 Calibration Observed vs SLSM Starshade 0.6735214 1.616574e-14
## cor5 Model vs SLSM Starshade 0.9972677 1.041258e-112##
## 2. Kolmogorov-Smirnov Test Results:## comparison ks_statistic p_value
## D Starshade Observed vs Calibration Observed 0.51 1.011651e-11
## D1 Starshade Observed vs Model 0.10 6.993742e-01
## D2 Starshade Observed vs SLSM Starshade 0.04 9.999982e-01
## D3 Calibration Observed vs Model 0.52 3.611663e-12
## D4 Calibration Observed vs SLSM Starshade 0.50 2.777589e-11
## D5 Model vs SLSM Starshade 0.06 9.937649e-01##
## 3. Root Mean Square Error Between Distributions:## comparison rmse
## 1 Starshade Observed vs Calibration Observed 1.07333580
## 2 Starshade Observed vs Model 0.16901537
## 3 Starshade Observed vs SLSM Starshade 0.06837033
## 4 Calibration Observed vs Model 1.21696978
## 5 Calibration Observed vs SLSM Starshade 1.10196579
## 6 Model vs SLSM Starshade 0.13266971##
## 4. Regression Analysis for Each Distribution:## source slope intercept r_squared p_value
## log_area Starshade Observed -0.62147529 2.1990516 0.8991446 1.285514e-50
## log_area1 Calibration Observed -0.06477496 0.2019875 0.3950164 2.546405e-12
## log_area2 Model -0.68339436 2.4479841 0.9030513 1.851215e-51
## log_area3 SLSM Starshade -0.63532983 2.2429598 0.8907273 6.559785e-49## [1] "\n5. Area Under Curve Analysis:\n"## # A tibble: 4 × 2
## source auc
## <chr> <dbl>
## 1 Calibration Observed 0.247
## 2 Model 4.10
## 3 SLSM Starshade 3.66
## 4 Starshade Observed 3.60## [1] "\n6. Distribution Summary Statistics:\n"## # A tibble: 4 × 6
## source mean_log_count median_log_count sd_log_count min_log_count
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 Calibration Observ… 0.0570 0 0.135 0
## 2 Model 0.918 0.654 0.944 0
## 3 SLSM Starshade 0.821 0.482 0.883 0
## 4 Starshade Observed 0.808 0.602 0.860 0
## # ℹ 1 more variable: max_log_count <dbl>8.2 Trial 10
## Trial 10 Edge Distribution Analysis Results##
## 1. Correlation Analysis:## comparison pearson_r p_value
## cor Starshade Observed vs Calibration Observed 0.9923160 9.350211e-91
## cor1 Starshade Observed vs Model 0.9912269 6.030821e-88
## cor2 Starshade Observed vs SLSM Starshade 0.9970189 7.403561e-111
## cor3 Calibration Observed vs Model 0.9737756 7.992211e-65
## cor4 Calibration Observed vs SLSM Starshade 0.9938810 1.381802e-95
## cor5 Model vs SLSM Starshade 0.9870822 9.365427e-80##
## 2. Kolmogorov-Smirnov Test Results:## comparison ks_statistic p_value
## D Starshade Observed vs Calibration Observed 0.34 1.908033e-05
## D1 Starshade Observed vs Model 0.09 8.127483e-01
## D2 Starshade Observed vs SLSM Starshade 0.05 9.996333e-01
## D3 Calibration Observed vs Model 0.41 1.001244e-07
## D4 Calibration Observed vs SLSM Starshade 0.35 9.570235e-06
## D5 Model vs SLSM Starshade 0.07 9.670685e-01##
## 3. Root Mean Square Error Between Distributions:## comparison rmse
## 1 Starshade Observed vs Calibration Observed 0.65600409
## 2 Starshade Observed vs Model 0.20110698
## 3 Starshade Observed vs SLSM Starshade 0.07462964
## 4 Calibration Observed vs Model 0.81652691
## 5 Calibration Observed vs SLSM Starshade 0.66037761
## 6 Model vs SLSM Starshade 0.22236853##
## 4. Regression Analysis for Each Distribution:## source slope intercept r_squared p_value
## log_area Starshade Observed -0.6502636 2.260122 0.8648647 2.206654e-44
## log_area1 Calibration Observed -0.3047132 1.041860 0.8289008 2.367129e-39
## log_area2 Model -0.7143903 2.539565 0.8857097 5.935652e-48
## log_area3 SLSM Starshade -0.6547185 2.257508 0.8422867 4.337441e-41## [1] "\n5. Area Under Curve Analysis:\n"## # A tibble: 4 × 2
## source auc
## <chr> <dbl>
## 1 Calibration Observed 1.60
## 2 Model 4.20
## 3 SLSM Starshade 3.53
## 4 Starshade Observed 3.58## [1] "\n6. Distribution Summary Statistics:\n"## # A tibble: 4 × 6
## source mean_log_count median_log_count sd_log_count min_log_count
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 Calibration Observ… 0.360 0 0.439 0
## 2 Model 0.940 0.533 0.996 0
## 3 SLSM Starshade 0.792 0.0750 0.936 0
## 4 Starshade Observed 0.804 0.301 0.917 0
## # ℹ 1 more variable: max_log_count <dbl>8.3 Trial 11
## Trial 11 Edge Distribution Analysis Results##
## 1. Correlation Analysis:## comparison pearson_r p_value
## cor Starshade Observed vs Calibration Observed 0.9630816 1.175188e-57
## cor1 Starshade Observed vs Model 0.9866425 4.779898e-79
## cor2 Starshade Observed vs SLSM Starshade 0.9895681 2.810222e-84
## cor3 Calibration Observed vs Model 0.9355902 4.226939e-46
## cor4 Calibration Observed vs SLSM Starshade 0.9671463 4.266290e-60
## cor5 Model vs SLSM Starshade 0.9932099 2.229302e-93##
## 2. Kolmogorov-Smirnov Test Results:## comparison ks_statistic p_value
## D Starshade Observed vs Calibration Observed 0.48 1.971901e-10
## D1 Starshade Observed vs Model 0.17 1.111333e-01
## D2 Starshade Observed vs SLSM Starshade 0.17 1.111333e-01
## D3 Calibration Observed vs Model 0.50 2.777589e-11
## D4 Calibration Observed vs SLSM Starshade 0.46 1.292286e-09
## D5 Model vs SLSM Starshade 0.06 9.937649e-01##
## 3. Root Mean Square Error Between Distributions:## comparison rmse
## 1 Starshade Observed vs Calibration Observed 1.0134880
## 2 Starshade Observed vs Model 0.1791888
## 3 Starshade Observed vs SLSM Starshade 0.2057564
## 4 Calibration Observed vs Model 0.9687954
## 5 Calibration Observed vs SLSM Starshade 0.8702850
## 6 Model vs SLSM Starshade 0.1507934##
## 4. Regression Analysis for Each Distribution:## source slope intercept r_squared p_value
## log_area Starshade Observed -0.7813268 2.8501815 0.9318638 5.698289e-59
## log_area1 Calibration Observed -0.2847471 0.9822747 0.8393564 1.070844e-40
## log_area2 Model -0.7282105 2.7050619 0.9033761 1.570240e-51
## log_area3 SLSM Starshade -0.7093808 2.5682215 0.8962912 5.052006e-50## [1] "\n5. Area Under Curve Analysis:\n"## # A tibble: 4 × 2
## source auc
## <chr> <dbl>
## 1 Calibration Observed 1.53
## 2 Model 4.81
## 3 SLSM Starshade 4.38
## 4 Starshade Observed 4.91## [1] "\n6. Distribution Summary Statistics:\n"## # A tibble: 4 × 6
## source mean_log_count median_log_count sd_log_count min_log_count
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 Calibration Observ… 0.345 0 0.408 0
## 2 Model 1.07 1.07 1.01 0
## 3 SLSM Starshade 0.980 0.717 0.983 0
## 4 Starshade Observed 1.10 1.04 1.06 0
## # ℹ 1 more variable: max_log_count <dbl>8.4 Trial 12
## Trial 12 Edge Distribution Analysis Results##
## 1. Correlation Analysis:## comparison pearson_r p_value
## cor Starshade Observed vs Calibration Observed 0.8856474 2.034191e-34
## cor1 Starshade Observed vs Model 0.9808596 1.882959e-71
## cor2 Starshade Observed vs SLSM Starshade 0.9473323 2.927345e-50
## cor3 Calibration Observed vs Model 0.9496741 3.334913e-51
## cor4 Calibration Observed vs SLSM Starshade 0.9772260 8.636027e-68
## cor5 Model vs SLSM Starshade 0.9905724 2.018030e-86##
## 2. Kolmogorov-Smirnov Test Results:## comparison ks_statistic p_value
## D Starshade Observed vs Calibration Observed 0.49 7.475143e-11
## D1 Starshade Observed vs Model 0.21 2.431031e-02
## D2 Starshade Observed vs SLSM Starshade 0.24 6.302223e-03
## D3 Calibration Observed vs Model 0.37 2.267454e-06
## D4 Calibration Observed vs SLSM Starshade 0.31 1.341096e-04
## D5 Model vs SLSM Starshade 0.07 9.670685e-01##
## 3. Root Mean Square Error Between Distributions:## comparison rmse
## 1 Starshade Observed vs Calibration Observed 1.1959266
## 2 Starshade Observed vs Model 0.4749725
## 3 Starshade Observed vs SLSM Starshade 0.6463391
## 4 Calibration Observed vs Model 0.7470201
## 5 Calibration Observed vs SLSM Starshade 0.6105653
## 6 Model vs SLSM Starshade 0.1778119##
## 4. Regression Analysis for Each Distribution:## source slope intercept r_squared p_value
## log_area Starshade Observed -0.8194974 2.9920279 0.9171047 8.542547e-55
## log_area1 Calibration Observed -0.2493649 0.8291678 0.7464043 5.891392e-31
## log_area2 Model -0.6280351 2.2044739 0.8812621 3.863310e-47
## log_area3 SLSM Starshade -0.5716532 1.9552916 0.8314698 1.126230e-39## [1] "\n5. Area Under Curve Analysis:\n"## # A tibble: 4 × 2
## source auc
## <chr> <dbl>
## 1 Calibration Observed 1.20
## 2 Model 3.56
## 3 SLSM Starshade 3.00
## 4 Starshade Observed 5.17## [1] "\n6. Distribution Summary Statistics:\n"## # A tibble: 4 × 6
## source mean_log_count median_log_count sd_log_count min_log_count
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 Calibration Observ… 0.271 0 0.379 0
## 2 Model 0.798 0.401 0.878 0
## 3 SLSM Starshade 0.675 0.0123 0.823 0
## 4 Starshade Observed 1.16 1.11 1.12 0
## # ℹ 1 more variable: max_log_count <dbl>## Trial 12 Surface Distribution Analysis Results##
## 1. Correlation Analysis:## comparison pearson_r p_value
## cor Starshade Observed vs Calibration Observed 0.9859644 5.323202e-78##
## 2. Kolmogorov-Smirnov Test Results:## comparison ks_statistic p_value
## D Starshade Observed vs Calibration Observed 0.12 0.4675586##
## 3. Root Mean Square Error Between Distributions:## comparison rmse
## 1 Starshade Observed vs Calibration Observed 0.4265422##
## 4. Regression Analysis for Each Distribution:## source slope intercept r_squared p_value
## log_area Starshade Observed -1.815463 8.791456 0.9580624 2.641805e-69
## log_area1 Calibration Observed -1.681296 8.392893 0.9160102 1.625447e-54## [1] "\n5. Area Under Curve Analysis:\n"## # A tibble: 2 × 2
## source auc
## <chr> <dbl>
## 1 Calibration Observed 20.8
## 2 Starshade Observed 21.2## [1] "\n6. Distribution Summary Statistics:\n"## # A tibble: 2 × 6
## source mean_log_count median_log_count sd_log_count min_log_count
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 Calibration Observ… 4.63 5.11 2.31 0
## 2 Starshade Observed 4.73 5.09 2.43 0
## # ℹ 1 more variable: max_log_count <dbl>9. Combined Analysis and Comparison
9.1 Cumulative Comparison
## All Trials Surface Distribution Analysis Results##
## 1. Correlation Analysis:## comparison pearson_r p_value
## cor Trial 9 vs Trial 10 0.9767104 2.554861e-67
## cor1 Trial 9 vs Trial 11 0.9605212 2.953926e-56
## cor2 Trial 9 vs Trial 12 0.9819394 1.122806e-72
## cor3 Trial 10 vs Trial 11 0.9817243 1.995089e-72
## cor4 Trial 10 vs Trial 12 0.9906245 1.539446e-86
## cor5 Trial 11 vs Trial 12 0.9710947 8.835377e-63##
## 2. Kolmogorov-Smirnov Test Results:## comparison ks_statistic p_value
## D Trial 9 vs Trial 10 0.07 0.9670685
## D1 Trial 9 vs Trial 11 0.13 0.3667264
## D2 Trial 9 vs Trial 12 0.05 0.9996333
## D3 Trial 10 vs Trial 11 0.13 0.3667264
## D4 Trial 10 vs Trial 12 0.07 0.9670685
## D5 Trial 11 vs Trial 12 0.16 0.1545381##
## 3. Root Mean Square Error Between Distributions:## comparison rmse
## 1 Trial 9 vs Trial 10 0.5892228
## 2 Trial 9 vs Trial 11 0.9925532
## 3 Trial 9 vs Trial 12 0.5236460
## 4 Trial 10 vs Trial 11 0.6850030
## 5 Trial 10 vs Trial 12 0.3781914
## 6 Trial 11 vs Trial 12 0.8432413##
## 4. Regression Analysis for Each Distribution:## source slope intercept r_squared p_value
## log_area Trial 9 -1.948892 9.125252 0.9367151 1.523466e-60
## log_area1 Trial 10 -1.850231 9.040215 0.9603213 1.750396e-70
## log_area2 Trial 11 -1.565777 8.799607 0.9329998 2.498670e-59
## log_area3 Trial 12 -1.815463 8.791456 0.9580624 2.641805e-69## [1] "\n5. Area Under Curve Analysis:\n"## # A tibble: 4 × 2
## source auc
## <chr> <dbl>
## 1 Trial 10 22.0
## 2 Trial 11 23.8
## 3 Trial 12 21.2
## 4 Trial 9 21.4## [1] "\n6. Distribution Summary Statistics:\n"## # A tibble: 4 × 6
## source mean_log_count median_log_count sd_log_count min_log_count
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 Trial 10 4.90 5.24 2.48 0
## 2 Trial 11 5.29 5.79 2.13 0
## 3 Trial 12 4.73 5.09 2.43 0
## 4 Trial 9 4.76 5.35 2.64 0
## # ℹ 1 more variable: max_log_count <dbl>## All Trials Edge Distribution Analysis Results##
## 1. Correlation Analysis:## comparison pearson_r p_value
## cor Trial 9 vs Trial 10 0.9929732 1.188271e-92
## cor1 Trial 9 vs Trial 11 0.9907104 9.827838e-87
## cor2 Trial 9 vs Trial 12 0.9866390 4.839999e-79
## cor3 Trial 10 vs Trial 11 0.9757956 1.651127e-66
## cor4 Trial 10 vs Trial 12 0.9704842 2.425167e-62
## cor5 Trial 11 vs Trial 12 0.9957379 2.909056e-103##
## 2. Kolmogorov-Smirnov Test Results:## comparison ks_statistic p_value
## D Trial 9 vs Trial 10 0.05 0.99963329
## D1 Trial 9 vs Trial 11 0.17 0.11113334
## D2 Trial 9 vs Trial 12 0.21 0.02431031
## D3 Trial 10 vs Trial 11 0.15 0.21055163
## D4 Trial 10 vs Trial 12 0.17 0.11113334
## D5 Trial 11 vs Trial 12 0.07 0.96706849##
## 3. Root Mean Square Error Between Distributions:## comparison rmse
## 1 Trial 9 vs Trial 10 0.1194225
## 2 Trial 9 vs Trial 11 0.3784343
## 3 Trial 9 vs Trial 12 0.4649738
## 4 Trial 10 vs Trial 11 0.3941772
## 5 Trial 10 vs Trial 12 0.4760085
## 6 Trial 11 vs Trial 12 0.1300165##
## 4. Regression Analysis for Each Distribution:## source slope intercept r_squared p_value
## log_area Trial 9 -0.6214753 2.199052 0.8991446 1.285514e-50
## log_area1 Trial 10 -0.6502636 2.260122 0.8648647 2.206654e-44
## log_area2 Trial 11 -0.7813268 2.850182 0.9318638 5.698289e-59
## log_area3 Trial 12 -0.8194974 2.992028 0.9171047 8.542547e-55## [1] "\n5. Area Under Curve Analysis:\n"## # A tibble: 4 × 2
## source auc
## <chr> <dbl>
## 1 Trial 10 3.58
## 2 Trial 11 4.91
## 3 Trial 12 5.17
## 4 Trial 9 3.60## [1] "\n6. Distribution Summary Statistics:\n"## # A tibble: 4 × 6
## source mean_log_count median_log_count sd_log_count min_log_count
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 Trial 10 0.804 0.301 0.917 0
## 2 Trial 11 1.10 1.04 1.06 0
## 3 Trial 12 1.16 1.11 1.12 0
## 4 Trial 9 0.808 0.602 0.860 0
## # ℹ 1 more variable: max_log_count <dbl>9.2 Binned Comparison
10. Multiple Line analysis
## All Lines Starshade Surface Model Distribution Analysis Results##
## 1. Correlation Analysis:## comparison pearson_r p_value
## cor 1 vs 2 0.9988358 7.564024e-131
## cor1 1 vs 3 0.9989636 2.552176e-133
## cor2 1 vs 4 0.9991493 1.607047e-137
## cor3 1 vs 5 0.9981329 8.397415e-121
## cor4 1 vs 6 0.9968097 2.044465e-109
## cor5 1 vs 7 0.9992770 5.555589e-141
## cor6 1 vs 8 0.9988692 1.823520e-131
## cor7 1 vs 9 0.9990585 2.302382e-135
## cor8 1 vs 10 0.9968905 5.832676e-110
## cor9 2 vs 3 0.9971344 1.071306e-111
## cor10 2 vs 4 0.9976550 5.872171e-116
## cor11 2 vs 5 0.9965330 1.196001e-107
## cor12 2 vs 6 0.9946640 1.717183e-98
## cor13 2 vs 7 0.9983562 1.644275e-123
## cor14 2 vs 8 0.9970609 3.700220e-111
## cor15 2 vs 9 0.9978239 1.511973e-117
## cor16 2 vs 10 0.9938425 1.876590e-95
## cor17 3 vs 4 0.9985084 1.412129e-125
## cor18 3 vs 5 0.9977402 9.603163e-117
## cor19 3 vs 6 0.9967342 6.428044e-109
## cor20 3 vs 7 0.9985922 8.307438e-127
## cor21 3 vs 8 0.9989090 3.146807e-132
## cor22 3 vs 9 0.9980707 4.178564e-120
## cor23 3 vs 10 0.9967482 5.206339e-109
## cor24 4 vs 5 0.9995119 2.453363e-149
## cor25 4 vs 6 0.9988176 1.618303e-130
## cor26 4 vs 7 0.9997190 4.352269e-161
## cor27 4 vs 8 0.9996894 5.934717e-159
## cor28 4 vs 9 0.9998563 2.327759e-175
## cor29 4 vs 10 0.9985817 1.195578e-126
## cor30 5 vs 6 0.9994688 1.546511e-147
## cor31 5 vs 7 0.9994843 3.603954e-148
## cor32 5 vs 8 0.9995238 7.277024e-150
## cor33 5 vs 9 0.9996181 1.473628e-154
## cor34 5 vs 10 0.9990339 8.161006e-135
## cor35 6 vs 7 0.9986209 3.027076e-127
## cor36 6 vs 8 0.9990423 5.309737e-135
## cor37 6 vs 9 0.9988178 1.604735e-130
## cor38 6 vs 10 0.9991555 1.122184e-137
## cor39 7 vs 8 0.9995994 1.528436e-153
## cor40 7 vs 9 0.9997220 2.560420e-161
## cor41 7 vs 10 0.9981863 2.027753e-121
## cor42 8 vs 9 0.9995264 5.556977e-150
## cor43 8 vs 10 0.9988575 3.009166e-131
## cor44 9 vs 10 0.9986334 1.940138e-127##
## 2. Kolmogorov-Smirnov Test Results:## comparison ks_statistic p_value
## D 1 vs 2 0.03 1.0000000
## D1 1 vs 3 0.03 1.0000000
## D2 1 vs 4 0.03 1.0000000
## D3 1 vs 5 0.04 0.9999982
## D4 1 vs 6 0.06 0.9937649
## D5 1 vs 7 0.03 1.0000000
## D6 1 vs 8 0.04 0.9999982
## D7 1 vs 9 0.03 1.0000000
## D8 1 vs 10 0.06 0.9937649
## D9 2 vs 3 0.04 0.9999982
## D10 2 vs 4 0.04 0.9999982
## D11 2 vs 5 0.05 0.9996333
## D12 2 vs 6 0.07 0.9670685
## D13 2 vs 7 0.04 0.9999982
## D14 2 vs 8 0.06 0.9937649
## D15 2 vs 9 0.05 0.9996333
## D16 2 vs 10 0.08 0.9062064
## D17 3 vs 4 0.03 1.0000000
## D18 3 vs 5 0.04 0.9999982
## D19 3 vs 6 0.04 0.9999982
## D20 3 vs 7 0.04 0.9999982
## D21 3 vs 8 0.03 1.0000000
## D22 3 vs 9 0.03 1.0000000
## D23 3 vs 10 0.05 0.9996333
## D24 4 vs 5 0.03 1.0000000
## D25 4 vs 6 0.04 0.9999982
## D26 4 vs 7 0.02 1.0000000
## D27 4 vs 8 0.02 1.0000000
## D28 4 vs 9 0.02 1.0000000
## D29 4 vs 10 0.05 0.9996333
## D30 5 vs 6 0.03 1.0000000
## D31 5 vs 7 0.03 1.0000000
## D32 5 vs 8 0.02 1.0000000
## D33 5 vs 9 0.03 1.0000000
## D34 5 vs 10 0.03 1.0000000
## D35 6 vs 7 0.05 0.9996333
## D36 6 vs 8 0.04 0.9999982
## D37 6 vs 9 0.05 0.9996333
## D38 6 vs 10 0.03 1.0000000
## D39 7 vs 8 0.02 1.0000000
## D40 7 vs 9 0.02 1.0000000
## D41 7 vs 10 0.05 0.9996333
## D42 8 vs 9 0.02 1.0000000
## D43 8 vs 10 0.04 0.9999982
## D44 9 vs 10 0.05 0.9996333##
## 3. Root Mean Square Error Between Distributions:## comparison rmse
## 1 1 vs 2 0.04560622
## 2 1 vs 3 0.03944914
## 3 1 vs 4 0.03633549
## 4 1 vs 5 0.06031709
## 5 1 vs 6 0.07218678
## 6 1 vs 7 0.03888501
## 7 1 vs 8 0.04315660
## 8 1 vs 9 0.04105515
## 9 1 vs 10 0.07106682
## 10 2 vs 3 0.07168801
## 11 2 vs 4 0.06417193
## 12 2 vs 5 0.07237352
## 13 2 vs 6 0.09106474
## 14 2 vs 7 0.04919926
## 15 2 vs 8 0.06610239
## 16 2 vs 9 0.05758095
## 17 2 vs 10 0.09753202
## 18 3 vs 4 0.04743684
## 19 3 vs 5 0.07060149
## 20 3 vs 6 0.07576008
## 21 3 vs 7 0.05579387
## 22 3 vs 8 0.04758050
## 23 3 vs 9 0.05937966
## 24 3 vs 10 0.07452611
## 25 4 vs 5 0.03960796
## 26 4 vs 6 0.04504994
## 27 4 vs 7 0.03031912
## 28 4 vs 8 0.02497469
## 29 4 vs 9 0.02235435
## 30 4 vs 10 0.04750144
## 31 5 vs 6 0.03103146
## 32 5 vs 7 0.02843356
## 33 5 vs 8 0.02972391
## 34 5 vs 9 0.02612048
## 35 5 vs 10 0.04105053
## 36 6 vs 7 0.04678188
## 37 6 vs 8 0.03814762
## 38 6 vs 9 0.04202460
## 39 6 vs 10 0.03396742
## 40 7 vs 8 0.02474454
## 41 7 vs 9 0.02011513
## 42 7 vs 10 0.05355944
## 43 8 vs 9 0.02505910
## 44 8 vs 10 0.04159827
## 45 9 vs 10 0.04546680##
## 4. Regression Analysis for Each Distribution:## source slope intercept r_squared p_value
## log_area 1 -0.5745947 1.991477 0.8626897 4.831235e-44
## log_area1 2 -0.5615357 1.951405 0.8707654 2.467110e-45
## log_area2 3 -0.5815099 2.014236 0.8589816 1.786614e-43
## log_area3 4 -0.5778383 1.990227 0.8490061 5.116960e-42
## log_area4 5 -0.5636019 1.932306 0.8397044 9.626891e-41
## log_area5 6 -0.5716532 1.955292 0.8314698 1.126230e-39
## log_area6 7 -0.5655892 1.948491 0.8516637 2.140208e-42
## log_area7 8 -0.5702904 1.962300 0.8465250 1.138847e-41
## log_area8 9 -0.5688896 1.957308 0.8475658 8.154343e-42
## log_area9 10 -0.5735963 1.962319 0.8304943 1.495185e-39## [1] "\n5. Area Under Curve Analysis:\n"## # A tibble: 10 × 2
## source auc
## <dbl> <dbl>
## 1 1 3.14
## 2 2 3.09
## 3 3 3.17
## 4 4 3.10
## 5 5 2.98
## 6 6 3.00
## 7 7 3.04
## 8 8 3.05
## 9 9 3.04
## 10 10 3.02## [1] "\n6. Distribution Summary Statistics:\n"## # A tibble: 10 × 6
## source mean_log_count median_log_count sd_log_count min_log_count
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 0.705 0.289 0.812 0
## 2 2 0.694 0.358 0.790 0
## 3 3 0.712 0.191 0.823 0
## 4 4 0.697 0.191 0.823 0
## 5 5 0.671 0.107 0.807 0
## 6 6 0.675 0.0123 0.823 0
## 7 7 0.682 0.191 0.804 0
## 8 8 0.686 0.163 0.813 0
## 9 9 0.684 0.199 0.811 0
## 10 10 0.678 0.0379 0.826 0
## # ℹ 1 more variable: max_log_count <dbl>## All Lines Calibration Surface Model Distribution Analysis Results##
## 1. Correlation Analysis:## comparison pearson_r p_value
## cor 1 vs 2 0.9951516 1.585809e-100
## cor1 1 vs 3 0.9980309 1.133750e-119
## cor2 1 vs 4 0.9996635 2.967063e-157
## cor3 1 vs 5 0.9972659 1.074680e-112
## cor4 1 vs 6 0.9977437 8.888355e-117
## cor5 1 vs 7 0.9963519 1.443638e-106
## cor6 1 vs 8 0.9912174 6.357962e-88
## cor7 1 vs 9 0.9974059 8.211316e-114
## cor8 1 vs 10 0.9960779 4.987475e-105
## cor9 2 vs 3 0.9990980 2.826783e-136
## cor10 2 vs 4 0.9956136 1.186185e-102
## cor11 2 vs 5 0.9989762 1.398791e-133
## cor12 2 vs 6 0.9988876 8.141502e-132
## cor13 2 vs 7 0.9995798 1.590111e-152
## cor14 2 vs 8 0.9990443 4.795013e-135
## cor15 2 vs 9 0.9990832 6.262543e-136
## cor16 2 vs 10 0.9988805 1.114875e-131
## cor17 3 vs 4 0.9980244 1.331972e-119
## cor18 3 vs 5 0.9994264 6.612416e-146
## cor19 3 vs 6 0.9993988 6.650110e-145
## cor20 3 vs 7 0.9994928 1.600257e-148
## cor21 3 vs 8 0.9973050 5.318698e-113
## cor22 3 vs 9 0.9994168 1.496608e-145
## cor23 3 vs 10 0.9989620 2.743538e-133
## cor24 4 vs 5 0.9976441 7.370042e-116
## cor25 4 vs 6 0.9976520 6.252802e-116
## cor26 4 vs 7 0.9964772 2.614028e-107
## cor27 4 vs 8 0.9917808 2.501950e-89
## cor28 4 vs 9 0.9978268 1.417424e-117
## cor29 4 vs 10 0.9960215 1.003350e-104
## cor30 5 vs 6 0.9986322 2.027655e-127
## cor31 5 vs 7 0.9990655 1.601072e-135
## cor32 5 vs 8 0.9975328 7.051565e-115
## cor33 5 vs 9 0.9991998 8.012992e-139
## cor34 5 vs 10 0.9989044 3.859015e-132
## cor35 6 vs 7 0.9993785 3.372592e-144
## cor36 6 vs 8 0.9964680 2.967844e-107
## cor37 6 vs 9 0.9991261 5.993121e-137
## cor38 6 vs 10 0.9989494 4.960029e-133
## cor39 7 vs 8 0.9981711 3.053264e-121
## cor40 7 vs 9 0.9995037 5.519521e-149
## cor41 7 vs 10 0.9990765 8.956911e-136
## cor42 8 vs 9 0.9970648 3.466921e-111
## cor43 8 vs 10 0.9977610 6.102946e-117
## cor44 9 vs 10 0.9983836 7.216465e-124##
## 2. Kolmogorov-Smirnov Test Results:## comparison ks_statistic p_value
## D 1 vs 2 0.06 0.9937649
## D1 1 vs 3 0.05 0.9996333
## D2 1 vs 4 0.02 1.0000000
## D3 1 vs 5 0.08 0.9062064
## D4 1 vs 6 0.05 0.9996333
## D5 1 vs 7 0.06 0.9937649
## D6 1 vs 8 0.07 0.9670685
## D7 1 vs 9 0.04 0.9999982
## D8 1 vs 10 0.08 0.9062064
## D9 2 vs 3 0.03 1.0000000
## D10 2 vs 4 0.07 0.9670685
## D11 2 vs 5 0.05 0.9996333
## D12 2 vs 6 0.04 0.9999982
## D13 2 vs 7 0.02 1.0000000
## D14 2 vs 8 0.03 1.0000000
## D15 2 vs 9 0.04 0.9999982
## D16 2 vs 10 0.03 1.0000000
## D17 3 vs 4 0.05 0.9996333
## D18 3 vs 5 0.06 0.9937649
## D19 3 vs 6 0.02 1.0000000
## D20 3 vs 7 0.02 1.0000000
## D21 3 vs 8 0.04 0.9999982
## D22 3 vs 9 0.03 1.0000000
## D23 3 vs 10 0.04 0.9999982
## D24 4 vs 5 0.09 0.8127483
## D25 4 vs 6 0.05 0.9996333
## D26 4 vs 7 0.06 0.9937649
## D27 4 vs 8 0.07 0.9670685
## D28 4 vs 9 0.04 0.9999982
## D29 4 vs 10 0.08 0.9062064
## D30 5 vs 6 0.06 0.9937649
## D31 5 vs 7 0.06 0.9937649
## D32 5 vs 8 0.04 0.9999982
## D33 5 vs 9 0.06 0.9937649
## D34 5 vs 10 0.04 0.9999982
## D35 6 vs 7 0.03 1.0000000
## D36 6 vs 8 0.05 0.9996333
## D37 6 vs 9 0.03 1.0000000
## D38 6 vs 10 0.03 1.0000000
## D39 7 vs 8 0.03 1.0000000
## D40 7 vs 9 0.03 1.0000000
## D41 7 vs 10 0.03 1.0000000
## D42 8 vs 9 0.05 0.9996333
## D43 8 vs 10 0.04 0.9999982
## D44 9 vs 10 0.05 0.9996333##
## 3. Root Mean Square Error Between Distributions:## comparison rmse
## 1 1 vs 2 0.08061827
## 2 1 vs 3 0.04924833
## 3 1 vs 4 0.01778867
## 4 1 vs 5 0.06143171
## 5 1 vs 6 0.04950316
## 6 1 vs 7 0.06588700
## 7 1 vs 8 0.10817392
## 8 1 vs 9 0.05213392
## 9 1 vs 10 0.06769087
## 10 2 vs 3 0.03571660
## 11 2 vs 4 0.07835248
## 12 2 vs 5 0.03250816
## 13 2 vs 6 0.04315720
## 14 2 vs 7 0.02461213
## 15 2 vs 8 0.03347406
## 16 2 vs 9 0.04698409
## 17 2 vs 10 0.03780540
## 18 3 vs 4 0.04949169
## 19 3 vs 5 0.02538749
## 20 3 vs 6 0.02480585
## 21 3 vs 7 0.02255071
## 22 3 vs 8 0.06117038
## 23 3 vs 9 0.02850054
## 24 3 vs 10 0.03200326
## 25 4 vs 5 0.05885528
## 26 4 vs 6 0.05018166
## 27 4 vs 7 0.06518483
## 28 4 vs 8 0.10606138
## 29 4 vs 9 0.04777213
## 30 4 vs 10 0.06794804
## 31 5 vs 6 0.03988339
## 32 5 vs 7 0.02958268
## 33 5 vs 8 0.05366749
## 34 5 vs 9 0.03778891
## 35 5 vs 10 0.03318666
## 36 6 vs 7 0.02772706
## 37 6 vs 8 0.07122050
## 38 6 vs 9 0.02927052
## 39 6 vs 10 0.03309176
## 40 7 vs 8 0.05017981
## 41 7 vs 9 0.03078581
## 42 7 vs 10 0.02992986
## 43 8 vs 9 0.07199508
## 44 8 vs 10 0.05542910
## 45 9 vs 10 0.04207640##
## 4. Regression Analysis for Each Distribution:## source slope intercept r_squared p_value
## log_area 1 -0.4799373 1.655257 0.8485806 5.874869e-42
## log_area1 2 -0.4913128 1.725389 0.8838731 1.297678e-47
## log_area2 3 -0.4839446 1.688698 0.8727120 1.171503e-45
## log_area3 4 -0.4782786 1.650797 0.8486298 5.781843e-42
## log_area4 5 -0.4866653 1.705628 0.8794854 8.006856e-47
## log_area5 6 -0.4805276 1.674285 0.8729008 1.089199e-45
## log_area6 7 -0.4857015 1.699302 0.8789826 9.821404e-47
## log_area7 8 -0.4926665 1.743552 0.8943796 1.237636e-49
## log_area8 9 -0.4752808 1.656676 0.8706598 2.567988e-45
## log_area9 10 -0.4818688 1.689285 0.8850458 7.886536e-48## [1] "\n5. Area Under Curve Analysis:\n"## # A tibble: 10 × 2
## source auc
## <dbl> <dbl>
## 1 1 2.58
## 2 2 2.79
## 3 3 2.70
## 4 4 2.58
## 5 5 2.74
## 6 6 2.66
## 7 7 2.73
## 8 8 2.86
## 9 9 2.64
## 10 10 2.72## [1] "\n6. Distribution Summary Statistics:\n"## # A tibble: 10 × 6
## source mean_log_count median_log_count sd_log_count min_log_count
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 0.581 0.143 0.684 0
## 2 2 0.625 0.297 0.686 0
## 3 3 0.605 0.252 0.680 0
## 4 4 0.580 0.121 0.681 0
## 5 5 0.616 0.252 0.681 0
## 6 6 0.598 0.235 0.675 0
## 7 7 0.612 0.275 0.680 0
## 8 8 0.641 0.375 0.684 0
## 9 9 0.593 0.199 0.668 0
## 10 10 0.610 0.318 0.672 0
## # ℹ 1 more variable: max_log_count <dbl>